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U2Net-Segmentation

Salient object segmentation for high‑quality foreground extraction.

U2‑Net is a machine learning model for salient object detection and foreground extraction. It uses a two‑level nested U‑structure (RSU blocks) to capture both local and global context at multiple scales, producing high‑quality binary foreground masks. The model is trained on the DUTS dataset and is well‑suited for background removal, portrait segmentation, and object extraction on mobile and edge devices.

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Technical Details

Input resolution:320x320
Model checkpoint:u2net.pth
Number of output classes:1 (salient foreground mask)
Number of parameters:44.0M

Applicable Scenarios

  • Background Removal
  • Portrait Segmentation
  • E-Commerce Product Imaging

License

Tags

  • real-time

Supported Compute Devices

  • Snapdragon X Elite CRD
  • Snapdragon X Plus 8-Core CRD
  • Snapdragon X2 Elite CRD

Supported Compute Chipsets

  • Snapdragon® X Elite
  • Snapdragon® X Plus 8-Core
  • Snapdragon® X2 Elite

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